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At least 541 records · Page 30Linked to original sources
PubMed1985

Alternative statistical models for the examination of clinical positron emission tomography/fluorodeoxyglucose data.

This article describes a method for partitioning metabolic variability found in positron emission tomography/[18F]fluorodeoxyglucose studies. For the 15 subjects examined, 74.8% of the total metabolic variability could be ascribed to individual differences in global metabolic rate, whereas 15.8% of the total variability was consistent regional variation or pattern across subjects. Subsequently, the method of Q-component analysis is described for the identification of strong- and weak-pattern subjects. In addition, a standardization procedure that amplifies the observed pattern by removing systematic individual differences is described. Finally, the implications of these findings and methods for future and clinical studies are discussed.

Adolescent↗
PubMed2003

Inductive reasoning in medicine: lessons from Carl Gustav Hempel's 'inductive-statistical' model.

The purpose of this paper is to discuss both the fundamental requirements of sound scientific explanations and predictions and common fallacies that occur in explaining and predicting medical problems. To this end, the paper presents Carl Gustav Hempel's 'covering-law' model (1948 and 1962) and reviews some of the criticism of the model. The strength of Hempel's model is that it shows that inductive arguments, when applied with the requirement of maximal specificity, can serve as explanations as well as predictions. The major weakness of the 'covering-law' model, its inability to portray causal relatedness, has been addressed by philosophers such as Wesley Salmon. While few philosophers today agree with the 'covering-law' model in its original formulation, there is widespread consensus that the law has made a central contribution to describing the fundamental requirements of sound scientific explanations. Applying this model and its revisions in the medical context may help uncover potentially undetected fallacies in reasoning when explaining and predicting medical problems.

Biomedical Research↗
PubMed1989

Hematopoietic death of unprotected man from photon irradiations: statistical modeling from animal experiments.

Most estimates of the radiation dose lethal to 50 per cent of a human population are based on historical data taken from well-known experiences reflecting inadequately known physical and biological conditions, or from medical procedures where individual patients received advantages of modern clinical care. It has been debated as to whether the experience of unprotected man would more closely reflect that of hospital patients or of the radiobiological studies with large animals. The issue at question is whether the apparent two-fold or more increased susceptibility of large animals to death from bone marrow damage (compared with the majority of estimates for man) is due more to true interspecies differences or the lack of medical support. This study is an attempt to assess the radiosensitivity of unprotected man in terms of the composite animal experiments. Based upon an extensive data base containing 121 separate animals studies using 13 different species, an estimate of the mortality dose-response relationship due to a uniform, continuous field of photon radiation is predicted for 70 kg unprotected man. Man is assumed to have a level of radiation sensitivity similar to that of the species represented in the data base, after adjustment for body weight. The mathematical model used includes fixed terms to account for effects of body weight and dose rate, and random terms reflecting inter- and intra-species variation and experimental error. Point predictions and 95 per cent prediction intervals are given for the LD05, LD10, LD25, LD50, LD75, LD90, and LD95, for dose rates ranging from 0.01 to 0.5 Gy/min, and treatment times ranging from about 2 min to about 24 h. At 1 cGy/min our point prediction of the LD50 is 299 cGy with an associated 95 per cent prediction interval of (168 cGy, 535 cGy). The analogous values at 50 cGy/min are 183 cGy and (103 cGy, 326 cGy).

Animals↗
PubMed1997

Statistical modeling, phylogenetic analysis and structure prediction of a protein splicing domain common to inteins and hedgehog proteins.

Inteins, introns spliced at the protein level, and the hedgehog family of proteins involved in eucaryotic development both undergo autocatalytic proteolysis. Here, a specific and sensitive hidden Markov model (HMM) of protein splicing domain shared by inteins and the hedgehog proteins has been trained and employed for further analysis. The HMM characterizes the common features of this domain including the position where a site-specific DNA endonuclease domain is inserted in the majority of the inteins. The HMM was used to identify several new putative inteins, such as that in the Methanococcus jannaschii klbA protein, and to generate a multiple sequence alignment of sequences possessing this domain. Phylogenetic analysis suggests that hedgehog proteins evolved from inteins. Secondary and tertiary structure predictions suggest that the domain has a structure similar to a beta-sandwich. Similarities between the serine protease cleavage mechanism and the protein splicing reaction mechanism are discussed. Examination of the locations of inteins indicates that they are not inserted randomly in an extein, but are often inserted at functionally important positions in the host proteins. A specific and sensitive HMM for a domain present in klbA proteins identified several additional bacterial and archaeal family members, and analysis of the site of insertion of the intein suggests residues that may be functionally important. This domain may play a role in formation of surface-associated protein complexes.

Algorithms↗
PubMed2002

The European NEAT program: an integrated approach using acamprosate and psychosocial support for the prevention of relapse in alcohol-dependent patients with a statistical modeling of therapy success prediction.

BACKGROUND: A multicenter, prospective study was conducted in five European countries to observe outcome in alcohol misusers treated for 24 weeks with acamprosate and various psychosocial support techniques, within the setting of standard patient care. METHODS: Patients diagnosed as alcohol dependent using DSM-III-R criteria were treated, for 24 weeks, with acamprosate and appropriate psychosocial support. Potential predictor variables were recorded at inclusion. Drinking behavior was monitored throughout; the proportion of cumulative abstinence days was the principal outcome measure. The influence of baseline clinical and demographic variables on outcome was assessed using multiple regression analysis. Adverse events were recorded systematically. RESULTS: A total of 1289 patients were recruited; 1230 took at least one dose of the drug and provided at least one set of follow-up data; 543 (42.1%)patients were observed for the full 24-week period. The overall proportion of cumulative abstinence days was 0.48. Multiple physical and psychiatric comorbidities and a history of drug addiction were negatively correlated with outcome, as were, to a lesser extent, multiple previous episodes of detoxification, unemployment, and living alone. Older age and stable employment were positively associated with outcome. The difference in the unadjusted proportion of cumulative abstinence days between countries was significant ( < 0.001) but less so when adjusted for the predictive factors identified in the multivariate model ( < 0.019). Overall, outcome was not influenced by the nature of the psychosocial support provided. Adverse events were generally mild, with gastrointestinal disorders, which occurred in 21.5% of patients, being the most frequent. CONCLUSIONS: This open-label study confirms the efficacy and safety of acamprosate in the treatment of alcohol dependence in the setting of standard patient care. Treatment benefit was observed irrespective of the nature of the psychosocial support provided. Predictors of the response to treatment were identified; their heterogeneous distribution within the study population explained, at least in part, the differences in outcome between countries.

Acamprosate↗
PubMed2004

Can we improve the prediction of stone-free status after extracorporeal shock wave lithotripsy for ureteral stones? A neural network or a statistical model?

PURPOSE: We evaluated whether an artificial neural network (ANN) can improve the prediction of stone-free status after extracorporeal shock wave lithotripsy (ESWL) (Dornier Medical Systems, Inc., Marietta, Georgia) for ureteral stones compared to a logistic regression (LR) model. MATERIALS AND METHODS: Between February 1989 and December 1998, 984 patients with ureteral stones, including 780 males and 204 females with a mean age +/- SD of 40.85 +/- 10.33 years, were treated with ESWL. Stone-free status at 3 months was determined by urinary tract plain x-ray and excretory urography. Of all patients 919 (93.3%) were free of stones. The impact of 10 factors on stone-free status was studied using an LR model and ANN. These factors were patient age and sex, renal anatomy, stone location, side, number, length and width, whether stones were de novo or recurrent, and stent use. An LR model was constructed and ANN was trained on 688 randomly selected patients (70%) to predict stone-free status at 3 months. The 10 factors were used as covariates in the LR model and as input parameters to ANN. Performance of the trained net and developed logistic model was evaluated in the remaining 296 patients (30%), who served as the test set. The sensitivity (percent of correctly predicted stone-free cases), specificity (percent of correctly predicted nonstonefree cases), positive predictive value, overall accuracy and average classification rate of the 2 techniques were compared. Relevant variables influencing the construction of the 2 models were compared. RESULTS: Evaluating the performance of the LR and ANN models on the test set revealed a sensitivity of 100% and 77.9%, a specificity of 0.0% and 75%, a positive predictive value of 93.2% and 97.2%, an overall accuracy of 93.2% and 77.7%, and an average classification rate of 50% and 76.5%, respectively. LR failed to predict any nonstone free cases. LR and ANN identified stone location and stent use as important factors in determining the outcome, while ANN also identified stone length and width as influential factors. CONCLUSIONS: ANN and LR could predict adequately those who would be stone-free after ESWL for ureteral stones. The neural network has a higher ability to predict those who fail to respond to ESWL.

Female↗